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University of Manchester: Clinical Data Science
| Institution | University of Manchester |
|---|---|
| Department | Faculty of Biology, Medicine and Health |
| Web | https://www.manchester.ac.uk |
| pgtaught.cbm@manchester.ac.uk | |
| Telephone | +44 (0)161 529 4563 |
| Study type | Taught |
Postgraduate Certificate - PgCert
Summary
This Clinical Data Science course was co-created with end users and industry partners to develop a flexible programme suitable for busy health and social care practitioners.
-
You will benefit from blended teaching that will provide a rich mixture of online and face-to-face learning opportunities.
-
Build your digital, data capabilities and confidence.
-
Develop your own data-based solutions to clinical problems.
-
Learn to work and communicate better with data centric professionals on digital transformation and research projects.
-
Develop fundamental data science skills for processing, analysing, and communicating using data.
| Level | RQF Level 7 |
|---|---|
| Entry requirements | We require an honours degree (minimum 2:1) or overseas equivalent or relevant work experience. Non-standard applications for the course from applicants who have significant relevant professional experience and/or where the academic qualification falls below a 2:1 degree will be considered on an individual basis, and may be admitted at the discretion of the Programme Director. |
| Location | Main Site University Recruitment And Adm Oxford Road Manchester M13 9PL |
Summary
This Clinical Data Science course was co-created with end users and industry partners to develop a flexible programme suitable for busy health and social care practitioners.
-
You will benefit from blended teaching that will provide a rich mixture of online and face-to-face learning opportunities.
-
Build your digital, data capabilities and confidence.
-
Develop your own data-based solutions to clinical problems.
-
Learn to work and communicate better with data centric professionals on digital transformation and research projects.
-
Develop fundamental data science skills for processing, analysing, and communicating using data.
| Level | RQF Level 7 |
|---|---|
| Entry requirements | We require an honours degree (minimum 2:1) or overseas equivalent or relevant work experience. Non-standard applications for the course from applicants who have significant relevant professional experience and/or where the academic qualification falls below a 2:1 degree will be considered on an individual basis, and may be admitted at the discretion of the Programme Director. |
| Location | Main Site University Recruitment And Adm Oxford Road Manchester M13 9PL |
Summary
We offer our PgCert Clinical Data Science units as individual continuing professional development (CPD) courses.
These units aim to empower healthcare professionals from across the health and social care workforce, from knowledge and library specialists to nurses, AHPs, healthcare scientists, doctors and beyond, to apply data science in practice and translate data into patient benefit.
Our CPD units will give professionals across the board the opportunity to develop their data science skills and drive digital transformation in their practice. Participants will bring with them their clinical, health and social care knowledge and experience, and the programme will provide the computer science methods and maths, stats and machine learning skills to allow practitioners to make use of their data, adding value to their clinical work to benefit patients.
We offer the following units:
Clinical Data Engineering introduces learners to data wrangling, data quality and data governance providing them with an understanding of structured and unstructured data formats, how data is modelled in various commonly used database systems, as well as an awareness of the role of the data engineer/data engineering in healthcare.
Maths, Stats and Machine Learning covers data analysis methods, including statistical learning (statistics and machine learning methods) supported by knowledge and understanding of the mathematical principles underpinning these methods.
Data Visualisation and Communication focuses on the theories of visualisation and how to explore and communicate data through visualisations that can be tailored for different audiences without unintentionally misleading or confusing the intended recipient.
Human Factors and Digital Transformation provides students with an overview of the process of capturing and presenting user requirements and implementing and evaluating systems in the clinical, health and social care environment.
| Level | RQF Level 7 |
|---|---|
| Entry requirements | We require an honours degree (minimum 2:1) or overseas equivalent or relevant work experience. Non-standard applications for the course from applicants who have significant relevant professional experience and/or where the academic qualification falls below a 2:1 degree will be considered on an individual basis, and may be admitted at the discretion of the Programme Director. |
| Location | Main Site University Recruitment And Adm Oxford Road Manchester M13 9PL |
Summary
We offer our PgCert Clinical Data Science units as individual continuing professional development (CPD) courses.
These units aim to empower healthcare professionals from across the health and social care workforce, from knowledge and library specialists to nurses, AHPs, healthcare scientists, doctors and beyond, to apply data science in practice and translate data into patient benefit.
Our CPD units will give professionals across the board the opportunity to develop their data science skills and drive digital transformation in their practice. Participants will bring with them their clinical, health and social care knowledge and experience, and the programme will provide the computer science methods and maths, stats and machine learning skills to allow practitioners to make use of their data, adding value to their clinical work to benefit patients.
We offer the following units:
Clinical Data Engineering introduces learners to data wrangling, data quality and data governance providing them with an understanding of structured and unstructured data formats, how data is modelled in various commonly used database systems, as well as an awareness of the role of the data engineer/data engineering in healthcare.
Maths, Stats and Machine Learning covers data analysis methods, including statistical learning (statistics and machine learning methods) supported by knowledge and understanding of the mathematical principles underpinning these methods.
Data Visualisation and Communication focuses on the theories of visualisation and how to explore and communicate data through visualisations that can be tailored for different audiences without unintentionally misleading or confusing the intended recipient.
Human Factors and Digital Transformation provides students with an overview of the process of capturing and presenting user requirements and implementing and evaluating systems in the clinical, health and social care environment.
| Level | RQF Level 7 |
|---|---|
| Entry requirements | We require an honours degree (minimum 2:1) or overseas equivalent or relevant work experience. Non-standard applications for the course from applicants who have significant relevant professional experience and/or where the academic qualification falls below a 2:1 degree will be considered on an individual basis, and may be admitted at the discretion of the Programme Director. |
| Location | Main Site University Recruitment And Adm Oxford Road Manchester M13 9PL |
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